A New Coverage Flight Path Planning Algorithm Based on Footprint Sweep Fitting for Unmanned Aerial Vehicle Navigation in Urban Environments

Abstract

This paper presents a new coverage flight path planning algorithm that finds collision-free, minimum length and flyable paths for unmanned aerial vehicle (UAV) navigation in three-dimensional (3D) urban environments with fixed obstacles for coverage missions. The proposed algorithm significantly reduces computational time, number of turns, and path overlapping while finding a path that passes over all reachable points of an area or volume of interest by using sensor footprints’ sweeps fitting and a sparse waypoint graph in the pathfinding process. We devise a novel footprints’ sweep fitting method considering UAV sensor footprint as coverage unit in the free spaces to achieve maximal coverage with fewer and longer footprints’ sweeps. After footprints’ sweeps fitting, the proposed algorithm determines the visiting sequence of footprints’ sweeps by formulating it as travelling salesman problem (TSP), and ant colony optimization (ACO) algorithm is employed to solve the TSP. Furthermore, we generate a sparse waypoint graph by connecting footprints’ sweeps’ endpoints to obtain a complete coverage flight path. The simulation results obtained from various scenarios fortify the effectiveness of the proposed algorithm and verify the aforementioned claims.

A Two-Stage Method for Target Searching in the Path Planning for Mobile Robots

“…As presented in Equation 15, if the boundary judgment parameter for grid i, i.e., E(i) calculated by Equation (16), is greater than 0, the grid i is the boundary grid, i.e., i ∈ Y. A is the set of all identical grids of the gird map.…”

“…calculated by Equation (16), is greater than 0, the grid i is the boundary grid, i.e., iY  . A is the set of all identical grids of the gird map.…”

“…More importantly, to improve efficiency, we propose to apply the ACO to find a near-optimal solution. ACO has been widely applied in many fields (e.g., [16][17][18]).…”

Special Issue on Mobile Robots Navigation

“…Trajectory planning is also a relevant technology for autonomous Unmanned Aerial Vehicles (UAV). Majeed et al [12] propose a flight path planning algorithm to find collision-free, minimum length and flyable paths for such vehicles in three-dimensional urban environments with fixed obstacles, for coverage missions. This problem consists in finding a low cost path that covers the free space of an area of interest with minimum overlapping.…”

Dynamic Optimization and Heuristics Based Online Coverage Path Planning in 3D Environment for UAVs

“…For instance, optimality is one of the major challenges for UAVs’ path planning, and it defines that the system should be time, cost, and energy-efficient. Other factors are path length, robustness, and collision avoidance [ 21 , 22 ]. In this sense, a standard solution is the use of two different approaches, that is, a global one responsible for finding solutions to the complex problem and a local solution for the collision avoidance of dynamic obstacles.…”